3 The pressures on organizations are at a point where analytics has evolved from a business initiative to a BUSINESS IMPERATIVE More organization are using analytics to create a competitive advantage And leaders are outperforming their competitors in key financial measures Respondents who believe analytics creates a competitive advantage 1.6x Revenue Growth % 70% increase % 2.0x EBITDA Growth % 2.5x Stock Price Appreciation Source: 2010 and 2011 datasets Massachusetts Institute of Technology. Analytics: The real-world use of big data Study conducted by IBM Institute for Business Value, in collaboration with Säid Business School at the University of Oxford. Source: Outperforming in a data-rich, hyper-connected world, IBM Center for Applied Insights study conducted in cooperation with the Economist Intelligence Unit and the IBM Institute of Business Value

4 ANALYTIC-DRIVEN ORGANIZATIONS are distinguished by their ability to leverage All information All information Transaction data Application data Machine data Social data Enterprise content At the point of impact All perspectives Past (historical, aggregated) Present (real-time) Future (predictive) All people All departments Experts and non-experts Executives and employees Partners and customers All decisions Major and minor Strategic and tactical Routine and exceptions Manual and automated 4

5 What do people say about big data? Big data is primarily about large datasets We will have to replace all older systems in the new world of big data Big data is only Hadoop Older transactional data does not matter anymore Data warehouses are a thing of the past Big data is for the internet savvy companies. Traditional businesses are immune We do not have the need or budget or skills, so we do not need to worry 5

8 Big Data Example Why you don't get taxis in Singapore when it rains? Zafar Anjum Oct. 3, It is common experience that when it rains, it is difficult to get a cab in Singapore Most people would think that this unavailability of taxis during rain is because of high demand for cab services. Big Data has a very surprising answer for you 8

14 Consumer products company improves information access across 30 different repositories Need Intuitive user interface for exploration and discovery across 30 different repositories Encompass all global offices and be deployed quickly for a lower total cost of ownership Provide secure search capabilities across sharepoint sites, intranet pages, wikis, blogs and databases Benefits Able to identify experts across all global offices and 125,000 users worldwide Eliminated duplicate work and effort being performed across all employees Improved discovery and findability across global organization Provided internal knowledge and information that has led to improved decision making 14

17 Ufone reduced churn and kept subscribers happy, helping ensure that campaigns are highly effective and timely Need To ensure that its marketing campaigns targeted the right customers, before they left the network To keep its higher usage customers happy with campaigns offering services and plans that were right for them Benefits Predictive analytics is expected to improve the campaign response rate from about 25% to at least 50% CDRs can be analyzed within 30 seconds, instead of requiring at least a day Expected to reduce churn by approximately 15-20% 17

19 IBM Institute for Business Value and the Saïd Business School partnered to benchmark global big data activities IBM Institute for Business Value IBM Global Business Services, through the IBM Institute for Business Value, develops fact-based strategies and insights for senior executives around critical public and private sector issues. Saïd Business School University of Oxford The Saïd Business School is one of the leading business schools in the UK. The School is establishing a new model for business education by being deeply embedded in the University of Oxford, a world-class university, and tackling some of the challenges the world is encountering. 19

20 The study showed four phases of adoption Big data adoption Educate Explore Engage Execute Focused on knowledge gathering and market observations Developing strategy and roadmap based on business needs and challenges Piloting big data initiatives to validate value and requirements Deployed two or more big data initiatives and continuing to applying advanced analytics Percentage of total respondents Percentage of total respondents Percentage of total respondents Percentage of total respondents 24% 47% 22% 6% When segmented into four groups based on current levels of big data activity, respondents showed significant consistency in organizational behaviors Total respondents n = 1061 Totals do not equal 100% due to rounding 20

22 Recommendations for getting started Assess which Use Case would you most benefit from? What part of the business would benefit from expanding the data set and analytics to provide more complete answers? What part of the business is not using analytics today, but would benefit from analytics for their user community or to fuel their processes using new information sources? What information do I collect today, or what analytics do I perform, that would be highly valuable as an information set to others? Assess existing skills. You may need to: Evolve your existing analytics and information capabilities Raise your corporate competency Get ready to address performance, scalability, simplicity and cost True value is gained from a hybrid of existing and new investments 22

25 Please note IBM s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM s sole discretion. Information regarding potential future products is intended to outline our general product direction and it should not be relied on in making a purchasing decision. The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or functionality. Information about potential future products may not be incorporated into any contract. The development, release, and timing of any future features or functionality described for our products remains at our sole discretion. Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user s job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here. 25

The 5 Game Changing Big Data Use Cases Data is the new Oil. Data is just like crude. It s valuable, but if unrefined it cannot really be used. Clive Humby, DunnHumby We have for the first time an economy

The Future of Business Analytics is Now! 1 The pressures on organizations are at a point where analytics has evolved from a business initiative to a BUSINESS IMPERATIVE More organization are using analytics

Exploiting Data at Rest and Data in Motion with a Big Data Platform Sarah Brader, sarah_brader@uk.ibm.com What is Big Data? Where does it come from? 12+ TBs of tweet data every day 30 billion RFID tags

Are You Ready for Big Data? Jim Gallo National Director, Business Analytics February 11, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

Are You Ready for Big Data? Jim Gallo National Director, Business Analytics April 10, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

VIEWPOINT High Performance Analytics Industry Context and Trends In the digital age of social media and connected devices, enterprises have a plethora of data that they can mine, to discover hidden correlations

IBM Software Thought Leadership White Paper June 2013 The top five ways to get started with big data 2 The top five ways to get started with big data Big data: A high-stakes opportunity Remember what life

IBM Software June 2014 Thought Leadership White Paper The top five ways to get started with big data 2 The top five ways to get started with big data Big data: A high-stakes opportunity Remember what life

IBM Content Analytics with Enterprise Search, Version 3.0 Highlights Enables greater accuracy and control over information with sophisticated natural language processing capabilities to deliver the right

Ellis Holman Why Big Data? Why Now? Information is at the Center of a New Wave of Opportunity 44x as much Data and Content Over Coming Decade 2020 35 zettabytes And Organizations Need Deeper Insights 1in3

The Bloor Group IBM AND NEXT GENERATION ARCHITECTURE FOR BIG DATA & ANALYTICS VENDOR PROFILE The IBM Big Data Landscape IBM can legitimately claim to have been involved in Big Data and to have a much broader

Business Intelligence Trends For 2013 10 Trends The last few years the change in Business Intelligence seems to accelerate under the pressure of increased business demand and technology innovations. Here

BEYOND BI: Big Data Analytic Use Cases Big Data Analytics Use Cases This white paper discusses the types and characteristics of big data analytics use cases, how they differ from traditional business intelligence

IBM Software Business Analytics Social Analytics Social Business Analytics Gaining business value from social media 2 Social Business Analytics Contents 2 Overview 3 Analytics as a competitive advantage

Big Data Putting data to productive use Fast Forward What is big data, and why should you care? Get familiar with big data terminology, technologies, and techniques. Getting started with big data to realize

Beyond Watson: The Business Implications of Big Data Shankar Venkataraman IBM Program Director, STSM, Big Data August 10, 2011 The World is Changing and Becoming More INSTRUMENTED INTERCONNECTED INTELLIGENT

Test Data Management in the New Era of Computing Vinod Khader IBM InfoSphere Optim Development Agenda Changing Business Environment and Data Management Challenges What is Test Data Management Best Practices

Holistic Approach to Big Data #4: 5 High Value Big Data Use Cases 1 At IBM, our product management, engineering, partner enablement, marketing, and other teams have all been working together to help to

IBM Analytical Decision Management Deliver better outcomes in real time, every time Highlights Organizations of all types can maximize outcomes with IBM Analytical Decision Management, which enables you

IBM SPSS Modeler Three proven methods to achieve a higher ROI from data mining Take your business results to the next level Highlights: Incorporate additional types of data in your predictive models By

5 Keys to Unlocking the Big Data Analytics Puzzle Anurag Tandon Director, Product Marketing March 26, 2014 1 A Little About Us A global footprint. A proven innovator. A leader in enterprise analytics for

Defining a Roadmap to Big Data Success Robert Stackowiak, Oracle Vice President, Big Data 17 November 2015 Safe Harbor Statement The following is intended to outline our general product direction. It is

Big Data Challenges and Success Factors Deloitte Analytics Your data, inside out Big Data refers to the set of problems and subsequent technologies developed to solve them that are hard or expensive to

1 Drive optimized customer interaction at the point of contact, based on predicted outcomes and behavior to achieve desired results. 2 3 Today s customers live out loud Age of the Empowered Customer Organizations

BIG DATA STRATEGY Rama Kattunga Chair at American institute of Big Data Professionals Building Big Data Strategy For Your Organization In this session What is Big Data? Prepare your organization Building

IBM Software Big Data Retail Capitalizing on the power of big data for retail Adopt new approaches to keep customers engaged, maintain a competitive edge and maximize profitability 2 Capitalizing on the

DATAMEER WHITE PAPER Beyond BI Big Data Analytic Use Cases This white paper discusses the types and characteristics of big data analytics use cases, how they differ from traditional business intelligence